resampling, interpolating matrix

Question

I\'m trying to interpolate some data for the purpose of plotting. For instance, given N data points, I\'d like to be able to generate a \"smooth\" plot, made up of 10*N or s

Answer 1

Here's a minimal example of 1d interpolation with scipy -- not as much fun as reinventing, but.
The plot looks like sinc, which is no coincidence: try google spline resample "approximate sinc".
(Presumably less local / more taps ⇒ better approximation, but I have no idea how local UnivariateSplines are.)

""" interpolate with scipy.interpolate.UnivariateSpline """
from __future__ import division
import numpy as np
from scipy.interpolate import UnivariateSpline
import pylab as pl

N = 10 
H = 8
x = np.arange(N+1)
xup = np.arange( 0, N, 1/H )
y = np.zeros(N+1);  y[N//2] = 100

interpolator = UnivariateSpline( x, y, k=3, s=0 )  # s=0 interpolates
yup = interpolator( xup )
np.set_printoptions( 1, threshold=100, suppress=True )  # .1f
print "yup:", yup

pl.plot( x, y, "green",  xup, yup, "blue" )
pl.show()

Added feb 2010: see also basic-spline-interpolation-in-a-few-lines-of-numpy